1 An Implementation Sanun Srisuk 42973003 of EdgeFlow.
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Transcript of 1 An Implementation Sanun Srisuk 42973003 of EdgeFlow.
4
Theory & Algorithm
is a pixel in an image.
is an edge energy at location s along the orientation theta.
is the probability of finding an image boundary in the direction theta from s.
is the probability of finding an image boundary in the direction theta+pi from s.
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Intensity Edges
The edge energy E(s, theta) at scale sigma is defined to be the magnitude of the gradient of the smoothed image , which is obtained by smoothing the original image I(x,y) with a Gaussian kernel
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Intensity Edges
P(s, theta) is the probability of finding an image boundary in the direction theta from s.
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Edge Flow Vector
where is a complex number with its magnitude representing the resulting edge energy and angle representing the flow direction.
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Conclusion
EdgeFlow using a predictive coding model to identify and integrate the direction of change in image attributes such as color, texture, and phase discontinuities, at each image location.